The goal of this observational study is to develop and evaluate a large language model (LLM)-based decision support system for exercise prescription in breast cancer patients, aiming to provide personalized decision-making support for postoperative breast cancer rehabilitation.

The main questions it aims to answer are:

How accurate, personalized, and safe are the exercise prescriptions generated by the fine-tuned LLM? How does the model's performance compare with other mainstream or non-fine-tuned models across different stages and subtypes of breast cancer? Participants are postoperative breast cancer rehabilitation patients treated at Sun Yat-sen Memorial Hospital of Sun Yat-sen University. They will have demographic, tumor, treatment, and physical fitness data collected; receive personalized exercise prescriptions automatically generated by the LLM-based system; and provide subjective evaluations on the feasibility and executability of the prescriptions.

Inclusion Criteria:

• Adult patients aged 18-75 years with early-stage breast cancer who have undergone surgical treatment, such as mastectomy or breast-conserving surgery.
• ECOG performance status of 0-1, with adequate physical condition to participate in rehabilitation assessment and exercise prescription activities.
• Availability of essential clinical data, including demographic characteristics, tumor stage and subtype, treatment history, and baseline physical fitness assessment.
• Able to communicate effectively, maintain stable follow-up contact, and voluntarily participate in evaluation and feedback on exercise prescriptions.

Exclusion Criteria:

• Presence of severe postoperative complications or comorbidities (e.g., uncontrolled cardiac or pulmonary disease) that may interfere with participation in rehabilitation or pose a safety risk.
• Significant physical or mobility impairments preventing the performance of prescribed exercises.
• Severe psychiatric illness or cognitive dysfunction that hinders cooperation with assessments or follow-up.
• Incomplete or missing key clinical data, making evaluation or follow-up impossible.
• Any other condition deemed inappropriate for participation by the investigators.

Patients with breast cancer who have completed primary surgery and entered the postoperative rehabilitation stage at Sun Yat-sen Memorial Hospital, Sun Yat-sen University (Guangzhou, China).All participants receive individualized exercise prescriptions generated by large language models under physician supervision and approval, and their feedback on the feasibility of these prescriptions is collected.